Enhancement of Capacity in a MC-CDMA based Cognitive Radio Network Using Non-Cooperative Game Model

Authors: Kalyani J. Kulkarni, Bharat S. Chaudhari

Abstract:

This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the Quality of Service (QoS) of Primary Users (PU), a novel method is proposed for the resource allocation of Secondary Users (SU). In this paper, we propose the unique Utility Function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the Cognitive Radio Network (CRN) and to minimize the interference scenario. Utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. Existence of Nash Equilibrium for the postulated game is established.

Keywords: Cognitive Networks, Game Theory, Nash Equilibrium, Resource Allocation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1109253

References:

[1] J. Mitola, “Cognitive radio: an integrated agent architecture for software defined radio,” PhD Thesis, Royal Institute of Technology, KTH, 2000.
[2] FCC: Cognitive Radio Technologies Proceedings, Web Page: http://www.fcc.gov/oet/cognitiveradio
[3] Baseem Zayen et.al, “Game Theory-based Resource Management Strategy for Cognitive Radio Networks”, EURECOM.
[4] Rong Chai et al, “Game Theory-based Joint Pricing and Resource Allocation for Cognitive Radio Networks with Imperfect Channel Information”, CHINACOM-2014.
[5] B. Zayen, A. Hayer et al, “Resource Allocation for Cognitive Radio Networks with a Beamforming User Selection Strategy”, Asilomar, Nov-1-4, 2009.
[6] Hao He, Jie Chen et al, “Game Theoretic Analysis of Joint Channel Selection and Power Allocation in Cognitive Radio Networks”, IEEE xplore-2009.
[7] Haibo Dai, Yongming Huang and Luxi Yang, "Game Theoretic Maxlogit Learning Approaches for Joint Base Station Selection and Resource Allocation in Heterogeneous Networks", IEEE J. in Selected Areas in Commun, Vol. 33, NO 6, June 2015.
[8] N. Omidvar, B. H. Khalaj, "A Game Theoretic Approach for Power Allocation in the Downlink of Cognitive Radio Networks", CAMAD- 2011.
[9] Farhad Meshkati, Vincent Poor and Stuart C. Schwartz, "Enery-Efficient Resource Allocation in Wireless Networks: An overview of Game- Theoretic Approaches" Project under National Science Foundation Grant
[10] M. Haddad, A. Hayer, "Downlink Distributed Binary Allocation for Cognitive Radio Networks", PMRC Cannes, 2008.